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» Soft-Supervised Learning for Text Classification
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EMNLP
2006
13 years 9 months ago
Boosting Unsupervised Relation Extraction by Using NER
Web extraction systems attempt to use the immense amount of unlabeled text in the Web in order to create large lists of entities and relations. Unlike traditional IE methods, the ...
Ronen Feldman, Benjamin Rosenfeld
DGO
2007
152views Education» more  DGO 2007»
13 years 9 months ago
Identifying and classifying subjective claims
To understand the subjective documents, for example, public comments on the government’s proposed regulation, opinion identification and classification is required. Rather than ...
Namhee Kwon, Liang Zhou, Eduard H. Hovy, Stuart W....
CIKM
2008
Springer
13 years 9 months ago
Identification of class specific discourse patterns
In this paper we address the problem of extracting important (and unimportant) discourse patterns from call center conversations. Call centers provide dialog based calling-in supp...
Anup Chalamalla, Sumit Negi, L. Venkata Subramania...
NIPS
2008
13 years 9 months ago
Regularized Learning with Networks of Features
For many supervised learning problems, we possess prior knowledge about which features yield similar information about the target variable. In predicting the topic of a document, ...
Ted Sandler, John Blitzer, Partha Pratim Talukdar,...
CIKM
2008
Springer
13 years 9 months ago
Web-scale named entity recognition
Automatic recognition of named entities such as people, places, organizations, books, and movies across the entire web presents a number of challenges, both of scale and scope. Da...
Casey Whitelaw, Alexander Kehlenbeck, Nemanja Petr...